Sublime

they experiment, they explore, they adjust, they readjust, but not just in terms of having some wondrous mathematical model of the situation and updating a parameter. They form a hypothesis, maybe they have multiple hypotheses or ideas about the situation they are in, and they put more belief in the ones that work over time and throw out hypotheses

“They have hired astronomers; they have hired mathematicians; they have hired physicists; they have even hired theologists. They never even interviewed an economist.”

This is a “rich get richer” sort of model in which the more a word is used in the past, the more likely it is that it will attract more use in the future.

The eminent professor of complexity Melanie Mitchell rightly points out that present-day AI systems have many limitations: they can’t transfer knowledge from one domain to another, provide quality explanations of their decision-making process, and so on.

New strategies, new things are coming and going and striving to survive and do well in a situation they mutually create. We can describe this algorithmically, but not easily by equations, not just because the situation is complicated to track but because new behaviors and categories of behavior are not easily captured by equations.

The answer derives from the fact that what is good for groups is not always good for the individuals comprising them. For example, both multicellular organisms and social insect colonies are functionally specialized and hierarchically organized collectives that are highly successful in maintaining and transmitting accumulated knowledge, in the form